MSE of partial replicate design [General Sta­tis­tics]

posted by ElMaestro  – Denmark, 2013-04-10 11:51 (4814 d 07:22 ago) – Posting: # 10389
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Hi d_labes,


❝ For the full replicate (2x2x4) design Chow and Liu mention (without an elaborate explanation)

  mse = 1/2*(s2wT + s2wR)


❝ For the partial replicate design (2x3x3) I have arrived with

  mse = 1/3*(s2wT + 2*s2wR)

❝ mostly empirical based on simulations (classical subject data sims without a subject-by-formulation interaction in the statistical model).

❝ Via these sims it could be verified that the formula for the full replicate design seems correct.


Did you analyse with a mixed model or with a (g)lm?
And if you did a mixed model, did you simulate with balanced sequences without missing period data?

❝ My questions are:

❝ Does any body know a way to derive the formulas theoretically?


In a mixed model -if that's you case cf above- you have a V where the diagonal is either
a. s2wT+s2bT or s2wT+s2bT (full repl.)
b. s2wT or s2wR+s2bR (partial repl.)
The within's are clasically referred to as the errors. Your formula corresponds to setting the average of all those error-sigma2's equal to the mean squared error (case of no missing periods). It is more like a definition - the mean squared error is in essence the mean/average of the squared errors, right?

❝ Or has anybody done simulations of the 2x3x3 design to verify my finding?

❝ Or is that all bullshit since we have to assume s2wT = s2wR if we use ANOVA (homogeneous variances)?

ANOVA requires an lm; I am not sure I get your context. Can you explain?

Pass or fail!
ElMaestro

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